Mathematical modeling and optimization of wave energy converters and arrays

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Title: Mathematical modeling and optimization of wave energy converters and arrays
Authors: Sarkar, Dripta
metadata.dc.contributor.advisor: Dias, Frederic
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Date: Aug-2015
Abstract: The aim of this work is to develop methodologies and understand the dynamics of waveenergy energy converters (WECs) in some problems of practical interest. The focus is ona well known WEC - the Oscillating Wave Surge Converter (OWSC). In the first work, amathematical model is described to analyze the interactions in a wave energy farm comprising of OWSCs. The semi-analytical method uses Green’s integral equation formulation and Green’s function, yielding hyper-singular integrals which are later solved using the Chebyshev polynomial of the second kind. A new methodology for the optimization of large wavefarms is then presented and the approach includes a statistical emulator, an active learning approach (Gaussian Process Upper Confidence Bound with Pure Exploration) and a genetic algorithm. The modular concept of the OWSC, which has emerged to address some of the shortcomings in the original design of the OWSC, is also described and investigated using a semi analytical approach for cylindrical modules. In another work, the dynamics of the OWSC near a straight coast is analyzed and for a particular case, a significant enhancement in the performance of the OWSC is observed. This interesting result motivated the following study, where it is investigated if a breakwater can artificially enhance the performance of the OWSC. Lastly, a new approach is presented to analyze the interactions between two different kind of WECs (an OWSC and a Heaving Wave Energy Converter), performing different modes of motion.
Type of material: Doctoral Thesis
Publisher: University College Dublin. School of Mathematical Sciences
Advisor: Ph.D.
Copyright (published version): 2015 the author
Keywords: Array;Hydrodyamics;Machine learning;Optimization;Oyster;Wave energy
Language: en
Status of Item: Peer reviewed
Appears in Collections:Mathematics and Statistics Theses

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